Fruits (Banana and Guava) datasets for non-destructive quality classifications

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This article creates fruit (banana and guava) image datasets for non-destructive quality classifications. All images were shot with a Redmi Note 10-Pro mobile camera in natural sunlight. All the images were captured at different angles and saved in JPG format. A total of 1738 original images were collected. The images were augmented to total 8740 images through data enhancement methods (image flipping horizontally, enhancing the image contrast and brightness, boosting the color of the images, and image rotation at 30 degrees). This dataset allows researchers to study different algorithms of machine learning or deep learning for quality classification of fruits.

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